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Experimental Measurement of Misperception in Political Beliefs

Published online by Cambridge University Press:  10 March 2021

Taylor N. Carlson  and
Seth J. Hill Open the ORCID record for Seth J. Hill [Opens in a new window]
Taylor N. Carlson
Affiliation:
Department of Political Science, Washington University in Saint Louis, One Brookings Drive, St. Louis, MO63130, USA
Seth J. Hill*
Affiliation:
Department of Political Science, University of California, San Diego, 9500 Gilman Drive #0521, La Jolla, CA92093-0521, USA
*
*Corresponding author. Email: [email protected]
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Abstract

Recent research suggests widespread misperception about the political views of others. Measuring perceptions often relies on instruments that do not separate uncertainty from inaccuracy. We present new experimental measures of second-order political beliefs. To carefully measure political (mis)perceptions, we have subjects report beliefs as probabilities. To encourage accuracy, we provide micro-incentives for each response. To measure learning, we provide information sequentially about the perception of interest. We illustrate our method by applying it to perceptions of vote choice in the 2016 presidential election. Subjects made inferences about randomly selected American National Election Study (ANES) respondents. Before and after receiving information about the other, subjects reported a probabilistic belief about the other’s vote. We find that perceptions are less biased than in previous work on second-order beliefs. Accuracy increased most with the delivery of party identification and report of a most important problem. We also find evidence of modest egocentric and different-trait bias.

Keywords

Political beliefsmisperceptionvote choiceexperimental methods
Type
Research Article
Information
Journal of Experimental Political Science , Volume 9 , Issue 2 , Summer 2022 , pp. 241 - 254
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Experimental Research Section of the American Political Science Association

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Footnotes

The experiments presented here are approved by the UCSD Human Research Protections Program. We thank David Broockman, Dan Butler, Jamie Druckman, Anthony Fowler, James Fowler, Federica Izzo, and Shiro Kuriwaki for their helpful discussion. The data, code, and any additional materials required to replicate all analyses in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at: doi:10.7910/DVN/OJ3HJE (Hill and Carlson, 2021). The authors declare no conflicts of interest. Support for this research was provided by the University of California San Diego Academic Senate.

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